代码搜索：minimum
找到约 5,594 项符合「minimum」的源代码
代码结果 5,594
www.eeworm.com/read/349842/10796686
m minimum_cost.m
function D = Minimum_Cost(train_features, train_targets, lambda, region)
% Classify using the minimum error criterion via histogram estimation of the densities
% Inputs:
% features- Train featur
www.eeworm.com/read/438912/7720517
png oor_minimum.png
www.eeworm.com/read/438912/7720543
png ._oor_minimum.png
www.eeworm.com/read/399996/7816646
m minimum_cost.m
function test_targets = Minimum_Cost(train_patterns, train_targets, test_patterns, lambda)
% Classify using the minimum error criterion via histogram estimation of the densities
% Inputs:
% trai
www.eeworm.com/read/397099/8068773
m minimum_cost.m
function test_targets = Minimum_Cost(train_patterns, train_targets, test_patterns, lambda)
% Classify using the minimum error criterion via histogram estimation of the densities
% Inputs:
% trai
www.eeworm.com/read/245941/12770788
m minimum_cost.m
function test_targets = Minimum_Cost(train_patterns, train_targets, test_patterns, lambda)
% Classify using the minimum error criterion via histogram estimation of the densities
% Inputs:
% trai
www.eeworm.com/read/245849/12777890
m minimum_phase.m
function wav=minimum_phase(amp,nsamp)
% Function computes minimum-phase wavelet with given amplitude spectrum
% INPUT
% amp amplitude spectrum
% nsamp number of samples of desired wavelet
% O
www.eeworm.com/read/330850/12864778
m minimum_cost.m
function test_targets = Minimum_Cost(train_patterns, train_targets, test_patterns, lambda)
% Classify using the minimum error criterion via histogram estimation of the densities
% Inputs:
% trai
www.eeworm.com/read/317622/13500831
m minimum_cost.m
function test_targets = Minimum_Cost(train_patterns, train_targets, test_patterns, lambda)
% Classify using the minimum error criterion via histogram estimation of the densities
% Inputs:
% trai
www.eeworm.com/read/316604/13520406
m minimum_cost.m
function D = Minimum_Cost(train_features, train_targets, lambda, region)
% Classify using the minimum error criterion via histogram estimation of the densities
% Inputs:
% features- Train featur